AI engines extract short answers from your content. They do not read pages whole. If your sections are not structured for clean extraction, the engine skips them, even when the underlying content is excellent. This is the most concrete craft change for getting mentioned by AI.
The biggest practical difference between writing for Google rankings and writing for AI mentions is structural.
Google's algorithm reads your page and decides where to rank it. Even buried sections can lift the page if the topic is well-covered overall. The page is the unit.
AI engines work differently. They scan for sections that contain a clean answer to a specific question, then quote those sections. The section is the unit. A great article with one quotable section gets cited. A great article with no quotable sections gets ignored.
The Two-Sentence Test
The simplest working test for AI quotability:
Take any section of your latest article. Can the main point be stated in two sentences without losing context?
If yes, an AI engine can extract and cite it cleanly. The two sentences become the citation.
If no, the engine skips that section, even when the surrounding content is excellent. There's nothing for it to extract that would make sense pulled out.
This isn't a stylistic preference. It's a mechanical consequence of how retrieval works. Models break content into chunks. Each chunk gets scored for relevance to a query. The best-scoring chunks get fed into the answer. If your chunks don't contain self-contained answers, they don't score.
H2 Headings as Ranking Units
Your H2 headings aren't formatting. They're the unit boundaries the AI uses to chunk your content.
This means a few things for how you write headings.
Descriptive headings beat clever ones. "Why Keyword Volume Is Misleading" beats "The Trap." The first matches a real query someone might type. The second requires reading the section to understand what it's about. The AI doesn't read everything. It scans for matches.
Headings that mirror real search queries are higher-value. If a section answers "how often should I publish?", title it that way (or close). The AI matches user questions to your headings before picking the best section.
One question per section. A section that tries to answer two related questions extracts poorly. Split it.
Answers at the Top of Each Section
The "inverted pyramid" structure used to be a journalism preference. It's now a retrieval requirement.
Lead each section with the answer. Then explain. Then give examples. Don't build up to the conclusion.
If the first two sentences of a section don't contain the core answer, an AI engine can't cite the section cleanly. It might quote your build-up paragraph, which won't make sense out of context. Or it skips the section entirely.
The pattern that works:
- Sentence 1 to 2: the answer, stated plainly
- Sentence 3 onward: explanation, nuance, examples, edge cases
Readers benefit from this too. Most don't read top-to-bottom. They scan headings, then scan the first lines of sections that catch their interest. If the answer is in the first lines, they get value fast. If it's buried, they leave.
Worked Example
A common pattern that fails extraction:
On Publishing Frequency
A lot of advice in the SEO space focuses on publishing consistently, with various recommendations ranging from daily to monthly schedules. The argument goes that consistency signals to Google that your site is active and producing fresh content, and there's some truth to that, but it ignores a more important factor. Quality almost always matters more than frequency, especially in 2026 with the new ranking systems Google has rolled out, which can detect generic content. So while you might think you need to publish three times a week to compete, that's often counterproductive if those posts are mediocre.
This section is "thinking out loud." There's no extractable answer in the first two sentences. An AI engine either picks something irrelevant or skips it.
The same content, restructured for citation:
On Publishing Frequency
Quality matters more than frequency. One genuinely useful post a month outperforms three mediocre posts a week.
The "publish consistently" advice was right when Google measured content velocity. It's not the lever now. Helpful Content scoring evaluates each post directly. Three weak posts hurt your overall trust signal more than they help with freshness.
If you have to choose: publish less, make each post genuinely better than what already ranks for that topic.
The first two sentences are quotable on their own. They answer the implied question ("how often should I publish?") in a way that makes sense pulled out of context. Everything after is supporting context for readers who want it.
The information in both versions is the same. Only the structure changed.
What This Isn't
This isn't AI optimization. It's the same clarity that's always made for better writing, just enforced more strictly.
Long, rambling sections that bury the answer in paragraph six were always weak writing. Editors used to fix this. AI retrieval now punishes it directly.
The cool thing is, the same structure helps every reader. People skim. They want answers, not preamble. They appreciate sections that get to the point. None of that is new advice. It's just more measurable now.
What This Means for You
Three things you can do this week, starting with content you've already written.
Pick your three highest-traffic articles. Read each section. Apply the two-sentence test to the section as it currently reads. Mark which sections pass and which don't.
Restructure the failing sections. Move the answer to the top. Trim the wind-up. The information stays the same. The order changes.
Update your headings. Replace clever-but-vague headings with descriptive ones that mirror real questions. If the heading doesn't tell a reader (or a machine) what the section answers, change it.
This is one round of editing per article. Not a full rewrite. Most teams find their best content has the right substance buried in the wrong structure. Fixing the structure surfaces what was already there.
Related Pages
- AI Mentions vs Google Rankings: the section overview
- How AI Ranking Actually Works: passage ranking on the Google side
- What Makes Content Rank: content quality signals across both surfaces